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<h1>Make plots using the base package</h1>

<p><em>by Sébastien Crouzet</em></p>

<p>This chapter is about basic (but already powerful) plotting with R.</p>

<h2>First: how to get help</h2>

<h3>The help() command</h3>

<pre><code>help(read.table)
# OR
?read.table
</code></pre>

<p>For a list of command containing a given word (here &ldquo;mean&rdquo;):</p>

<pre><code>help.search(&#39;mean&#39;)
</code></pre>

<h3>CRAN task views</h3>

<p>The CRAN is the main repository for R packages. There is a lot of contributions to it so this can be tricky to explore or find what you are looking for if you don&#39;t have a precise idea. Fortunately, R users (experts in each field) are maintaining the <a href="http://cran.r-project.org/web/views/">CRAN task views</a>, which consists in organizing all the contributions following big meaningful topics.</p>

<h3>Useful resources on the web</h3>

<p><a href="http://www.statmethods.net/">statmethods.net</a><br/>
<a href="http://stackoverflow.com/questions/tagged/r">stackoverflow</a></p>

<h2>R base graphics</h2>

<h3>High-level graphic functions</h3>

<p>First, using the dataframe <em>pressure</em> available directly when called from R. We will plot the 2 variables (temperature on the x axis and pressure on the y axis) and then overlay some text.</p>

<pre><code class="r">pressure
</code></pre>

<pre><code>##    temperature pressure
## 1            0   0.0002
## 2           20   0.0012
## 3           40   0.0060
## 4           60   0.0300
## 5           80   0.0900
## 6          100   0.2700
## 7          120   0.7500
## 8          140   1.8500
## 9          160   4.2000
## 10         180   8.8000
## 11         200  17.3000
## 12         220  32.1000
## 13         240  57.0000
## 14         260  96.0000
## 15         280 157.0000
## 16         300 247.0000
## 17         320 376.0000
## 18         340 558.0000
## 19         360 806.0000
</code></pre>

<pre><code class="r">plot(pressure)
text(150, 600, &quot;Pressure (mm Hg)\nversus\nTemperature (Celsius)&quot;)
</code></pre>

<p><img src="" alt="plot of chunk unnamed-chunk-1"/> </p>

<p>To have more example of that, you can run </p>

<pre><code>example(plot).
</code></pre>

<p>Or to have more example of basic R graphic capabilities, try the following commands:</p>

<pre><code>example(barplot)
example(boxplot)
example(dotchart)
example(coplot)
example(hist)
example(fourfoldplot)
example(stars)
example(image)
example(contour)
example(filled.contour)
example(persp)    
</code></pre>

<p>This has probably filled your workspace with random stuff, please clear everything before now (the simplest is to click the little brush on the workspace part of your RStudio).</p>

<h3>Polishing your plot or adding info with low-level graphic functions</h3>

<p>vs. <strong>low-level</strong>  Usually, you will try to do as much as you can using a basic high-level function (such sd plot()) and then adjust the output graph using low-level ones (such as titles(), lines() or points()).</p>

<p>And a more complex one</p>

<pre><code class="r">layout(matrix(c(1:6), 3, 2, byrow = FALSE))
# par(mfrow=c(3, 2))

# Scatterplot
x &lt;- c(0.5, 2, 4, 8, 12, 16)
y1 &lt;- c(1, 1.3, 1.9, 3.4, 3.9, 4.8)
y2 &lt;- c(4, 0.8, 0.5, 0.45, 0.4, 0.3)
par(las = 1, mar = c(4, 4, 2, 4))
plot.new()
plot.window(range(x), c(0, 6))
lines(x, y1)
lines(x, y2)
points(x, y1, pch = 16, cex = 2)
points(x, y2, pch = 21, bg = &quot;white&quot;, cex = 2)
par(col = &quot;grey50&quot;, fg = &quot;grey50&quot;, col.axis = &quot;grey50&quot;)
axis(1, at = seq(0, 16, 4))
axis(2, at = seq(0, 6, 2))
axis(4, at = seq(0, 6, 2))
box(bty = &quot;u&quot;)
mtext(&quot;Travel Time (s)&quot;, side = 1, line = 2, cex = 0.8)
mtext(&quot;Responses per Travel&quot;, side = 2, line = 2, las = 0, cex = 0.8)
mtext(&quot;Responses per Second&quot;, side = 4, line = 2, las = 0, cex = 0.8)
text(4, 5, &quot;Bird 131&quot;)
par(mar = c(5.1, 4.1, 4.1, 2.1), col = &quot;black&quot;, fg = &quot;black&quot;, col.axis = &quot;black&quot;)

# Histogram Random data
Y &lt;- rnorm(50)
# Make sure no Y exceed [-3.5, 3.5]
Y[Y &lt; -3.5 | Y &gt; 3.5] &lt;- NA
x &lt;- seq(-3.5, 3.5, 0.1)
dn &lt;- dnorm(x)
par(mar = c(4.5, 4.1, 3.1, 0))
hist(Y, breaks = seq(-3.5, 3.5), ylim = c(0, 0.5), col = &quot;grey80&quot;, freq = FALSE)
lines(x, dnorm(x), lwd = 2)
par(mar = c(5.1, 4.1, 4.1, 2.1))

# Barplot
par(mar = c(2, 3.1, 2, 2.1))
midpts &lt;- barplot(VADeaths, col = grey(0.5 + 1:5/12), names = rep(&quot;&quot;, 4))
mtext(sub(&quot; &quot;, &quot;\n&quot;, colnames(VADeaths)), at = midpts, side = 1, line = 0.5, 
    cex = 0.5)
text(rep(midpts, each = 5), apply(VADeaths, 2, cumsum) - VADeaths/2, VADeaths, 
    col = rep(c(&quot;white&quot;, &quot;black&quot;), times = 2:3, cex = 0.8))
par(mar = c(5.1, 4.1, 4.1, 2.1))

# Boxplot
par(mar = c(3, 4.1, 2, 0))
boxplot(len ~ dose, data = ToothGrowth, boxwex = 0.25, at = 1:3 - 0.2, subset = supp == 
    &quot;VC&quot;, col = &quot;grey90&quot;, xlab = &quot;&quot;, ylab = &quot;tooth length&quot;, ylim = c(0, 35))
mtext(&quot;Vitamin C dose (mg)&quot;, side = 1, line = 2.5, cex = 0.8)
boxplot(len ~ dose, data = ToothGrowth, add = TRUE, boxwex = 0.25, at = 1:3 + 
    0.2, subset = supp == &quot;OJ&quot;, col = &quot;grey70&quot;)
legend(1.5, 9, c(&quot;Ascorbic acid&quot;, &quot;Orange juice&quot;), bty = &quot;n&quot;, fill = c(&quot;grey90&quot;, 
    &quot;grey70&quot;))
par(mar = c(5.1, 4.1, 4.1, 2.1))

# Persp
x &lt;- seq(-10, 10, length = 30)
y &lt;- x
f &lt;- function(x, y) {
    r &lt;- sqrt(x^2 + y^2)
    10 * sin(r)/r
}
z &lt;- outer(x, y, f)
z[is.na(z)] &lt;- 1
# 0.5 to include z axis label
par(mar = c(0, 0.5, 0, 0), lwd = 0.1)
persp(x, y, z, theta = 30, phi = 30, expand = 0.5, col = &quot;grey80&quot;)
par(mar = c(5.1, 4.1, 4.1, 2.1), lwd = 1)

# Piechart
par(mar = c(0, 2, 1, 2), xpd = FALSE, cex = 0.5)
pie.sales &lt;- c(0.12, 0.3, 0.26, 0.16, 0.04, 0.12)
names(pie.sales) &lt;- c(&quot;Blueberry&quot;, &quot;Cherry&quot;, &quot;Apple&quot;, &quot;Boston Cream&quot;, &quot;Other&quot;, 
    &quot;Vanilla&quot;)
pie(pie.sales, col = gray(seq(0.4, 1, length = 6)))
</code></pre>

<p><img src="" alt="plot of chunk unnamed-chunk-2"/> </p>

<p>Multivariate data</p>

<pre><code class="r"># Awful way to position multiple plots here (using oma) Won&#39;t lay things
# out nicely on different sized device or different output format (i.e.
# where line heights differ)
par(cex = 0.6)
pairs(iris[1:4], oma = c(18, 4, 4, 4), panel = function(x, y, ...) {
    points(x, y, lwd = 0.1, pch = &quot;.&quot;)
})
par(cex = 1)

par(new = TRUE)
par(omi = c(0, 0, 4.7, 0), mfrow = c(1, 2), mfg = c(1, 1), xpd = NA)
par(mar = c(1, 1, 0, 1))
palette(grey(0.5 + 1:8/24))
stars(mtcars[1:8, 1:7], len = 0.8, cex = 0.5, draw.segments = TRUE, xpd = NA)

par(mar = c(0, 1, 1, 1))
# Terrible hack to add empty lines to data set names to try to get
# labelling right in small size
dm &lt;- dimnames(Titanic)
dm$Sex &lt;- c(&quot;Male\n\n&quot;, &quot;Female\n\n&quot;)
dm$Survived &lt;- c(&quot;No\n&quot;, &quot;Yes\n&quot;)
dm$Age &lt;- c(&quot;Child\n&quot;, &quot;Adult\n&quot;)
dimnames(Titanic) &lt;- dm
mosaicplot(~Sex + Age + Survived, data = Titanic, off = rep(5, 3), ylab = &quot;&quot;, 
    main = &quot;&quot;, color = c(&quot;light grey&quot;, &quot;dark grey&quot;))
</code></pre>

<p><img src="" alt="plot of chunk unnamed-chunk-3"/> </p>

<pre><code class="r">plot(tapply(iris$Sepal.Length, iris$Species, sd))
</code></pre>

<p><img src="" alt="plot of chunk unnamed-chunk-4"/> </p>

<p>To create a pdf file where the figure will be drawn, and also have a figure with &ldquo;subplots&rdquo;:</p>

<pre><code class="r">pdf(&quot;MyFirstFigure.pdf&quot;, width = 9, height = 6)
layout(matrix(c(1:6), 2, 3, byrow = TRUE))
</code></pre>

<p>How to declare new colors:</p>

<pre><code class="r">orangeSeb = rgb(red = 0.96, green = 0.64, blue = 0.1, names = &quot;orangeSeb&quot;)
blueSeb = rgb(red = 0.2, green = 0.29, blue = 0.59, names = &quot;blueSeb&quot;)
</code></pre>

<p>Make a scatterplot with a linear fit.</p>

<pre><code class="r">plot(meanRT[Task == &quot;visage&quot; &amp; Type == &quot;original&quot;], accuracy[Task == &quot;visage&quot; &amp; 
    Type == &quot;original&quot;], xlim = c(0, 300), ylim = c(50, 100), bty = &quot;n&quot;, xlab = &quot;Mean SRT (ms)&quot;, 
    ylab = &quot;Accuracy (%)&quot;, col = orangeSeb)
</code></pre>

<pre><code>## Error: object &#39;meanRT&#39; not found
</code></pre>

<pre><code class="r">mylinefit = lm(meanRT[Task == &quot;visage&quot; &amp; Type == &quot;original&quot;] ~ accuracy[Task == 
    &quot;visage&quot; &amp; Type == &quot;original&quot;])
</code></pre>

<pre><code>## Error: object &#39;meanRT&#39; not found
</code></pre>

<pre><code class="r"># abline(mylinefit) lines(y = accuracy[Task==&#39;visage&#39; &amp; Type==&#39;original&#39;],
# x = mylinefit$fitted.values)
res = cor.test(meanRT[Task == &quot;visage&quot; &amp; Type == &quot;original&quot;], accuracy[Task == 
    &quot;visage&quot; &amp; Type == &quot;original&quot;])
</code></pre>

<pre><code>## Error: object &#39;meanRT&#39; not found
</code></pre>

<pre><code class="r">text(20, 60, paste(&quot;r = &quot;, round(res$p.value, 3)))
</code></pre>

<pre><code>## Error: object &#39;res&#39; not found
</code></pre>

<pre><code class="r">title(&quot;ORIGINAL&quot;)
</code></pre>

<pre><code>## Error: plot.new has not been called yet
</code></pre>

<h2>Links</h2>

<p><a href="http://gallery.r-enthusiasts.com/">R graph gallery</a> (with the code to generate the graphs)</p>

<p>Another excellent resource on the web, where several of the examples I used are coming from (with code examples):<br/>
1. <a href="http://www.stat.auckland.ac.nz/%7Epaul/RGraphics/chapter1.html">An Introduction to R Graphics</a><br/>
2. <a href="http://www.stat.auckland.ac.nz/%7Epaul/RGraphics/chapter2.html">Simple Usage of Traditional Graphics</a><br/>
3. <a href="http://www.stat.auckland.ac.nz/%7Epaul/RGraphics/chapter3.html">Customizing traditional graphics</a></p>

<h2>Exercises</h2>

<h2>- plot an image</h2>

</body>

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